Image processing device

ABSTRACT

An image processing device for every frame of a moving or still image including an uptake device to take the image data of the pixel unit from the image which photographed a subject, a histogram generating device to generate the histogram of the brightness after having disintegrated the data in the particular color space, read out the image by a predetermined pattern according to color, and set the brightness of the pixel of the particular position of the pattern based on the mean histogram of a pixel removed (lifted) from a particular position in the pattern.

TECHNICAL FIELD

This invention relates to an image processing device which converts an image containing a mixture of extremely bright and dark parts into a clear, easily viewed picture.

BACKGROUND ART

A surveillance camera may operate for 24 hours a day therefore, extremely bright images and extremely dark images are recorded every moment.

The general automatic gain control of the camera often cannot keep up with an extremely large change. Also, when an extremely dark part and bright part are mixed within the same picture, such as an indoor window, it cannot be dealt with by the automatic gain control.

As a conventional image evaluation technique, a method is known that uses a histogram to make a graph using a number of pixels, according to the brightness of each colour.

This method shows the pixel distribution in the image, it displays the detail of a shadow (the left-hand portion of the histogram), a halftone (the center of the histogram) and the highlight (the right-hand portion of the histogram), and judges whether this detail makes sufficient amendment to an image for it to be clearly seen.

For example, an imaging device is described in Prior art 1. This imaging device comprises; an imaging element to output an electrical signal performing photoelectric conversion of an optics image, signal processing means to generate a video signal processing electrical signal output by said imaging element, a histogram circuit which generates a histogram from a video signal output by the said signal processing means, and an exposure control means using a histogram detected by the said histogram circuit.

An image processing method is described in Prior art 2. This image processing method comprises; a process to generate an image by reading a light from a manuscript, a process to make a histogram of the density distribution from the image data, a process to generate a density amendment curve based on a ratio of the number of the data of the part which came close to the light and shade at both ends of the density distribution corresponding to the number of the entire data of the image data, a process to make a density amendment of the image data using the density amendment curve.

An imaging device is described in Prior art 3. This imaging device provides an imaging means and a gradation correcting means, the imaging means images a subject, and the image data of the subject is acquired, the gradation correcting means makes a harmony amendment to a pixel portion which is a predetermined pixel portion of the imaging image consisting of image data acquired by imaging means and to a pixel portion comprising the pixels that have a brightness level which is within a predetermined range.

PRIOR ART Patented Documents

-   [Prior Art 1] Japanese Laid Open Patent Publication (tokkai) No.     2002-142150 -   [Prior Art 2] Japanese Laid Open Patent Publication (tokkai) No.     2003-051944 -   [Prior Art 3] Japanese Laid Open Patent Publication (tokkai) No.     2007-124087

DISCLOSURE OF THE INVENTION Object of the Invention

Regarding Prior art 1, for example, when a still image is photographed, for the histogram of the imaging image generated by histogram section 25, it is retrieved using a CPU that is the luminance range where it is distributed over the brightness of the useful data range and the luminance range where it is not distributed over the brightness of the useless data.

This is difficult for the still image photography in real time when a CPU with a large processing capacity is not used with the picture which contains a large number of pixels.

Regarding Prior art 2, in the case of color mode, a high level image processing system is required for processing a histogram which synthesized R, G, B colors, and in the case of gray mode, a high grade image processing system is also required for processing a histogram which generates a histogram only for G color.

That is, when a high capacity host computer is not used, there are problems in that the processing time is greatly increased.

Regarding Prior art 3, a gamma amendment (gradation amendment) is performed according to an amendment curve using the histogram of the imaging image.

For example, when distribution has two peaks, enough gradation is assigned to a recorded image while maintaining overall gradation relations on a dark part (a long-distance background) and a bright part (the subject of the short distance), for the purpose of eliminating the useless data range (the luminance range over which brightness is not distributed) that was on the high intensity side by expanding the range of both peaks on the high intensity side.

However, by this method, there is a problem in that it is not practical for moving image, because it takes too much time to calculate a histogram of the whole picture with a large number of pixels.

Means of Solving the Problem

In order to solve the above-mentioned problems, the image processing device for every frame of the moving or still image comprising an uptake means to take the image data of the pixel unit from the image which photographed a subject, and a histogram generating means to generate a histogram of the brightness after having disintegrated the data in the particular color space, and read out the image by a predetermined pattern according to color, then determine the brightness of the pixel of the particular position of the pattern based on the histogram, the brightness of the pixel is calculated based on the algorithm that assumed the loop number of times a pixel value.

It is preferable to move a pixel and a predetermined pattern according to a predetermined rule: after having set the brightness of the pixel of the particular position, when generating the histogram of the predetermined pattern after the movement, subtract a histogram of the pixel which is not duplicated by prior or after movement, and add only a histogram of a pixel newly added to the area of the predetermined pattern.

Alternatively, in the case where the whole predetermined pattern is in the picture, it is preferable to move a pixel and a predetermined pattern according to maintaining a predetermined overlap portion under the predetermined rule.

Effect of the Invention

The algorithm of the present invention is an algorithm to obtain an equal (the same) result with a simple algorithm without having to take a 2 pass (route) method.

It is possible to perform a real-time processing of VGA animation by combining a graphic board and cheap microcomputer or personal computer, also, using hardware equipped for FPGA is possible, and processing with DSP is possible, too.

SIMPLE EXPLANATION OF THE DRAWINGS

FIG. 1 A figure showing the basic example of the system

FIG. 2 A figure showing the comparative example of the histogram

FIG. 3 A figure showing the positional relations of a picture and the predetermined reading pattern

FIG. 3 b A figure showing the positional relations of a picture and the predetermined reading pattern

FIG. 3 c A figure showing the positional relations of a picture and the predetermined reading pattern

FIG. 3 d A figure showing the positional relations of a picture and the predetermined reading pattern

FIG. 3 e A figure showing the positional relations of a picture and the predetermined reading pattern

FIG. 3 f A figure showing the positional relations of a picture and the predetermined reading pattern

FIG. 4 A figure showing the foundation stone example of the history optimization of the pixel unit detection

FIG. 5 A figure showing an example of scanning every two lines

FIG. 6 A figure showing the example of a plurality of distributed processing

FIG. 7 A figure showing the comparative example of the image before and after the amendment

PREFERRED EMBODIMENT OF THE INVENTION

The best mode for carrying out the invention is described below based on drawing sheet details.

Note that in the present invention, an old-type graphics board is not used. It is desirable to use a graphics board based on a multi-core GPU having 120 or more cores per processor.

As shown in FIG. 1, the present system is basically a microcomputer or a personal computer equipped with a graphics board, CPU1 comprises frame grabber 6, an image is taken in this frame grabber 6 through system bus 3 and interface 4 such as a graphics board, ROM2 a, RAM2 b, PCI.

Also, for operating the devices, the present system has operation devices 7 such as buttons or external connections ports 8 such as serial port through I/O interface 5.

The graphics board is comprised of GPU9 having one parallel computation cell, processing frame buffer 11, output frame buffer 12, indication output circuit 13.

The image processing method of the present invention has the above constitution when processing either every frame of an animation (moving picture) or a still image.

That is, the present invention comprises an uptake means and a histogram generating means, the uptake means take the image data of the pixel unit from the image which photographed a subject, the histogram generating means generates a histogram of the brightness after disintegrating the image data that took in the particular color space.

The image is read out by a predetermined pattern according to a color by the uptake means, the mean histogram around the pixel of the particular position in the pattern is generated using the histogram generating means, and the brightness of the pixel of the particular position is set using this mean histogram.

GPU9 receives instructions from CPU1 and processes the image data in processing frame buffer 11 according to the instructions to each cell, in order that a processing result is written in at frame buffer 12 for output.

There are plural cells, in performing parallel computations, the instructions from a CPU are processed at the number of cells simultaneously.

The CPU1 of the computer transfers software corresponding to the processing of this matter to RAM2 b from ROM2 a at the start, and the software carries out the processes. The software initiated repeats a series of tasks as follow.

(1) An image is taken from a frame grabber

(2) The image taken in is transferred to the processing frame buffer 11 on the graphics board

(3) Handling of this matter is indicated to GPU

(4) A cell in GPU performs instructions by parallel computation

(5) Wait until all processing results are written in at a frame buffer for output

(6) Processing result is displayed

A plurality of color space can be represented with frame buffer 12 for processing and frame buffer 11 for output, YCbCr, HSV, Lab, HLS are intended for use in this matter

Indication output circuit 13 converts the details of frame buffer 12 for output becoming the color space expression into the video signal that is adapted to a display. Indication output circuit 13 supports a plurality of video signals, analog RGB is general, DVI, a component (D1-D4), YC separation, composites can be output.

The image processing method of the present invention treats an image of every moving picture frame or still image, comprises an uptake means and a histogram generating means, the uptake means takes the image data of the pixel unit from the image which photographed a subject, the histogram generating means generates a histogram of the brightness after disintegrating the image data that took in the particular color space.

The image is read out by a predetermined pattern according to a color by the uptake means, the mean histogram around the pixel of the particular position in the pattern is generated using the histogram generating means, and the brightness of the pixel of the particular position is set using this mean histogram.

The image brightness information is read out with predetermined reading pattern 16, the brightness of the pixel of the particular position of reading pattern 16 is set, on the basis of the mean histogram except for the pixel of the particular position in reading pattern 16.

Also, when predetermined reading pattern 16 moves in the horizontal scanning direction, the compatibility of data is guaranteed even if reading pattern 16 is moved on the image, when the reading patterns 16 are overlapped before movement and after movement in an overlap area.

By the above, it is possible to basically process dynamic data as a stream, by using the GPU of the graphics board for calculation rather than the CPU of the computer. To put the operation processing process in a nutshell, data are analyzed in real time, and highly precise, high-speed processing can be performed.

In the operation process in the kernel: pipeline processing is used so that the parallel computation of dynamic data is possible, a GPU used in the present embodiment becomes a 128 scalar processors with an arithmetic unit that enables parallel computation, whereas the core number of a conventional multi-core CPU is 2-4 cores.

Even if a scalar processor is used, the real-time processing of the image has vast computational complexity. Therefore there is the example in which a GPU of 960 cores is used for 3D graphics, but, in the present conditions even it has insufficient computing power.

The present invention enables the histogram optimization of a moving image in real time even using a GPU the performance of which is insufficient for 3D processing.

FIG. 2 shows the comparative example of the histogram, FIG. 2 (a) shows an example original histogram, there are two peaks to the right and left, FIG. 2 (b) shows a histogram which is equalized and has become relatively flat

Generally, when the brightness of the image is not uniformly distributed the image is improved through adjusting the brightness distribution by averaging the histogram, or widening the contrast by extending a low image of the contrast using gamma curve conversion having S-curve, then, the dark point is darkened, the bright point is lightened, so that it is worked to turn it into a well-controlled image.

If the histogram is averaged, as for the dark part, the detail becomes cleat However, there are many dark parts, thus, a part of the sky and a part in contact with the sky become too bright, and detail is impaired.

To reduce the damage to the detail of this transition section, for example, divide the area into a part of the sky (bright part), a part of the border of the sky and the ground and a part of the ground, and average the histogram in for each part.

Also, it is possible to extract a detail of the medium portion of the image where brightness and darkness are extreme, by scanning an image beforehand and detecting the brightness distribution, and averaging the histogram in an area distributed.

This is a 2 pass (step) method, because an image is scanned to divide the area and scanned once again to average the histogram.

The said method cannot be carried out quickly when a moving image is processed in real time, and the algorithm to divide an area becomes difficult and complicated.

Also, the same level memory which stores image of a division result is required, because it is necessary to convert an image according to a table after the full screen has been scanned and a brightness conversion table has been made.

In addition, in the said method, it is necessary to scan an image four times in total, twice for dividing the area and twice for averaging the histogram.

However, as describe in the details below, the benefit of the present invention is that the averaging of the histogram can be processed in only one pass, because, in assuming a calculation area to be one pixel, a calculation process for dividing an area is not necessary.

FIG. 3 shows the position relations of a picture and the predetermined reading pattern, FIG. 3 a shows the whole of a display picture displaying an image and shows a reading pattern 16 in the display picture 15.

In the present invention, the image processing method is adopted is described below in detail.

That is, Set the brightness of the pixel of the particular position, and move the pixel and the predetermined pattern according to a predetermined rule, when generating the mean histogram of the predetermined pattern after the movement, subtract the histogram of the pixel which is not duplicated before and after of moving and add the histogram of the pixel which is newly put to the area of the predetermined pattern.

Herein, when it is assumed that the display picture is comprised of the pixels of m lines and n rows, if sequence is represented in (line, row), a picture begins with pixel (0, 0), the first line terminates in the pixel (1, n), and the final pixel is represented in (m, n).

FIG. 3 (b) shows a reading pattern, a particular pixel is set as the target pixel 17 in the reading pattern 16.

FIG. 3 (c) is the figure which shows the processing image area in the display picture.

To carry out averaging the histogram, in the case that all of reading pattern 16 is not in the display picture 15, different histogram average algorithms must to be used, as a result, extra processing time is required.

Thus, in the present invention, a processing picture area is limited to the area that is narrower than the display picture 15, and all of reading pattern 16 is put to the display picture 15 every time, as a result, the need to make a judgment as to whether or not all of reading pattern 16 is in the display picture 15 can therefore be omitted.

Specifically, for example, when the reading pattern 16 is comprised of 7 cells, set a non-scan area of 3 cell width in each line and each row, and assume an area surrounded by (3, 3), (1, n-3), (m-3, n-3), (3, n-3) as a processing picture area, thereby, reading pattern 16 will exist in the display picture 15 each time.

When processing to average the histogram of all pixels in the area surrounded by (3, 3), (1, n-3), (m-3, n-3), (3, n-3) is finished, the data of an area surrounded by (4, 4), (4, 6), (6, 6), (6, 4) are copied and translational movement is made in the area surrounded by (1, 1), (1, 3), (3, 3), (1, 3).

That is, the data of the pixel (1, 1) are replaced for the data of the pixel (4, 4) and the data of the pixel (3, 3) are replaced for the data of the pixel (6, 6).

Likewise, the data of an area surrounded by (m-5, 4), (m-5, 6), (m-3, 4), (m-3, 6) are copied and translational movement is made in the area surrounded by (m-2, 1), (m-2, 3), (m3, 3), (m, 1).

FIG. 3 (e) illustrates the method of data copy of 1˜3 lines and m-2˜m except four corners of the display picture, that is, copy the data of an area surrounded by pixel (4, 4), (4, n-3), (3, n-3), (6, 4), and shift to the upper direction for 3 cells, and replace for the data of the area surrounded by pixel (1, 4), (1, n-3), (3, n-3), (3, 4).

Likewise, copy the data of an area surrounded by pixel (m-5, 4), (m-5, n-3), (m-3, n-3), (m-3, 4), and shift to the down direction for 3 cells, and replace the data of the area surrounded by pixel (m-5, 4), (m-5, n-3), (m-3, n-3) for the data of the area surrounded by pixel (m-2, 4), (m-2, n-3), (m, n-3), (m, 4).

FIG. 3 (f) illustrates the method of data copy of 1˜3 rows and n-2˜n except four corners of the display picture, that is, copy the data of an area surrounded by pixel (4, 4), (4, 6), (m-3, 6), (m-3, 4), and shift to the left direction for 3 cells, and replace the data of the area surrounded by pixel (4, 4), (4, 6), (m-3, 6), (m-3, 4) for the data of the area surrounded by pixel (4, 1), (4, 3), (m-3, 3), (m-3, 1).

Likewise, copy the data of an area surrounded by pixel (4, n-5), (4, n-3), (m-3, n-3), (m-3, n-5), and shift to the right direction for 3 cells, and replace the data of the area surrounded by pixel (4, n-5), (4, n-3), (m-3, n-3), (m-3, n-5) for the data of the area surrounded by pixel (4, n-2), (4, n), (m-3, n), (m-3, n-2).

Herein, the histogram of this invention is defined as the distribution of the brightness of each pixel in the histogram extraction area.

When the brightness is 8 bits of information, it becomes 256 sequences showing the brightness.

As described above, regarding a too bright or too dark image, the detail extraction becomes possible by averaging the histogram, regarding the image in which bright parts and dark parts are mixed, the detail of the transition section can be extracted by averaging the histogram in each divided areas separately.

However, it can be expected that the algorithm to divide an area will be complicated, also, handling of fading is required to connect the border of the area on an image naturally,—additionally, detail can be extracted more naturally when an area is small and multiply divided. However, when an area is too narrow, the connection with the periphery of the area becomes unnatural, and a detail of the same size as the area cannot be extracted.

Thus, the inventor of the present invention realized that, if a calculation area is assumed as being one pixel, to decide the brightness of the pixel, the calculation for averaging of the histogram is performed using the neighboring histogram.

The following advantages are achieved by assuming a calculation area of one pixel.

A calculation process dividing an area becomes unnecessary, and averaging of the histogram will be earned out in just 1 pass.

It is not necessary to take into consideration the composition of the border area.

The problem of losing a detail the same size as the area can be avoided.

However, a calculation to average the histogram is required to all pixels (VGA approximately 300,000), an algorithm to reduce this computational complexity is required.

A subscript number of the sequence as brightness, the number of pixels with the brightness is stored in each element.

Generally, scan an area after having cleared the sequence and, to gain the brightness of the pixel, it is implemented by incrementing an element of each sequence.

In this algorithm, calculate the histogram by a pixel unit, then the above described calculation is required to calculate the histogram of the first pixel (4, 4). However, the second target pixel 17 (4, 5) only moves one row to the right, it is not necessary to recalculate the histogram. Simply subtract the histogram of the left row pixels from the total histogram of the reading pattern (16) and add the histogram of the right row pixels.

In this way, calculating an average of the histogram by a pixel unit can greatly simplify the process for updating the histogram

Also, since the above processing is independent for each line, high-speed processing is enabled with parallel computation using the pixel carried by the general graphics board. When the graphics board has 256 cells, processing is completed in the processing time for 2 lines.

To calculate the average of the histogram, generate a conversion table of the brightness based on the histogram sequence calculated in the foregoing paragraph, and calculate a brightness according to the conversion table.

The calculation algorithm (C-language) using the above described conversion table is as follows: (The brightness assumes 8 bits, “hist” represents a histogram sequence, “table” represents a conversion table sequence, “total” represents the number of pixels in the area)

for ( i=n=0; i<256; i++) { n = n + hist[ i ]; table[ i ] = n * 256 / total; }

Then, calculate the brightness of the area using the following algorithm based on the conversion table.

for ( i=0; i<dy; i++) { for ( j=0; j<dx; j++) { p = get_pix( x + j , y + i); p = table[ p ]; put_pix( x + j , y + i , p ); } }

In the above, x,y is an area origin, dx,dy is an area range, get_pix(x,y) is a function that acquires the brightness of the former image, put_pix(x,y,p) is a function that stores brightness after the calculation to conversion image.

Herein, in this algorithm, the calculation area is one pixel, thus, the loop calculation described previously is not necessary. And regarding to the conversion, it is enough to convert the brightness of the pixel which is a target of the calculation. So that the algorithm of the processing equal to paragraph (0061) and (0062) is as follows, In the case of a black-and-white image.

p = get_pix( x , y ); for ( i=n=0; i<=p; i++){ n = n + hist[ i ]; } p = n * 256 / total; put_pix( x , y , p );

In the case of a black-and-white image, the present algorithm itself can just be adapted. However, in the case of a colored image, it is usually necessary to divide the colour information and the brightness information.

Usually, the averaging of the histogram is processed to each plane of RGB. However, in the present invention, it can be achieved with the processing that is equal to a black-and-white image, because a color space used in JPEG or MPEG is isolated by the basic function of the graphics board, and only the necessary plane need be processed.

Correspondence of color space and the plane to be processed, for example, following is considered.

Y C b C r: Y plane H S V: V plane L a b: L plane H L S: L plane

Select an input image from the above described color space according to the internal expression of the graphics board, and carry out the processing of only the brightness plane. Thereby it can avoid the need for the RGB conversion processing, to repeat of the same process three times and to change the hue.

FIG. 4 explains the principle of the optimization of the histogram which is detected by a pixel unit. In the present embodiment, as shown in FIG. 4 (a), calculate the histogram of the selected pixels which comprise the reading pattern 16, and calculate the value of the target pixel 17 according to the algorithm of paragraph (0064), subsequently, the selected pixels for calculate the histogram shift to the right.

FIG. 4 (b) shows condition where the target pixel 17 is moved to the right by one pixel, and in this condition, the selected pixels from the second row to the seventh row among the selected pixels from the first row to the seventh row those are already used for the calculation of the histogram, the selected pixels from the second row to the seventh row are common with FIG. 4 (a), and the pixels of the eighth row are added to the selected pixels from the second row to the seventh row.

Therefore, the pixels from the second row to the seventh row and the pixels of the eighth row become a new object of the calculation. However, it is not necessary to calculate the details of all the pixels again.

That is, subtract the first row data from a total value of the histogram which are in the area surrounded by pixel (1, 1), (1, 7), (7, 1), (7, 7), and add the data of the eighth row to the data from the second row to the seventh row, as above, thus it can easily calculate the histogram.

In FIG. 4 (b), the area surrounded with a solid line is the calculation area for the next calculation, and the pixel of line 4 row 5 is the target pixel 17 which is the subject of the next brightness calculation, and the area except for the target pixel (4, 5) from the area surrounded with pixels (1, 2), (1, 8), (7, 2), (7, 8) becomes the calculation area.

As described above, the actual calculation can be processed in a short time, because only the first row histogram is subtracted from the previously calculated value and added to the fifth row histogram.

FIG. 5 shows an embodiment which calculate by moving a pixel one by one. However, the present invention is not limited to the above. That is, under the condition when the whole predetermined pattern in the display, it is possible to effect a dramatic reduction by keeping an overlap portion before and after the moving pattern when the pattern moves according to a predetermined rule in the horizontal scanning direction, this reduction makes it possible to speed up the processing while improving the contrast of the whole display.

The detail of the high-speed processing is explained below.

At first as shown In FIG. 5 (a), in the area surrounded with pixel (1, 1), (1, 5), (5, 1), (5, 5), the area drawn in hatching, that is, the area from pixel (1, 1) to (5, 1), the area of pixel (1, 3) and (2, 3), the area of pixel (4, 3) and (5, 3), and the area from pixel (1, 5) to (5, 5), calculate the mean of the pixels and determine the value of the pixel (3, 3) which is the target pixel 17.

Subsequently, as shown in FIG. 5 (b), move the reading pattern for by 2 pixels horizontally, assume pixel (3, 5) as a target pixel, and calculate the mean of the pixels in the area surrounded with pixel (1, 3), (1, 7), (5, 3), (5, 7), that is, the area from pixel (1, 3) to (5, 3), the area of pixel (1, 5) and (2, 5), the area of pixel (4, 5) and (5, 5), and the area from pixel (1, 7) to (5, 7), and determine the value of the pixel (3, 5) which is the target pixel 17.

FIG. 6 shows an embodiment of the parallel computation. It can shorten calculation time by dispersing to a plurality of calculation cells and perform parallel computation.

In FIG. 6 (a), the area surrounded by pixel (1, 1), (1, 5), (5, 1), (5, 5) is the first reading pattern 16, and the area surrounded by pixel (6, 1), (6, 5), (10, 1), (10, 5) is the second pattern 16 a.

In the first reading pattern 16, calculate the histogram of the pixel (1, 1)˜(5, 1), pixel (1, 3) and (2, 3), pixel (4, 3) and (5, 3) and pixel (1, 5)˜(5, 5), and determine the value of the pixel (3, 3) using the mean value of the pixels.

In the second reading pattern 16 a, calculate the histogram of the pixel (6, 1)˜(10, 1), pixel (6, 3) and (7, 3), pixel (9, 3) and (10, 3) and pixel (6, 5)˜(10, 5), and determine the value of the pixel (8, 3) using the mean value of the pixels.

FIG. 7 (a) shows an example of an image before processing, it shows a photograph of a bridge which is just before a forest. Overall the picture is dark

FIG. 7 (b) shows the example of the image after processing with the present algorithm, the bridge just before the forest is clearly seen.

It can process an image in a short time by using the algorithm for image processing of the present invention. Thus, not only the still image in FIG. 5 but also the video image which photographed a dark scene can be reproduced in real time. It is also an effective technique for amending a video image which is a mix an extremely bright and dark parts in the same picture, such as an image from a surveillance camera or an image of an indoor window

INDUSTRIAL APPLICABILITY

It can achieve a high sensitivity that is almost the sensitivity of a night scope not only for surveillance cameras but also for general video cameras, by using the image processing method of the present invention without the need for an expensive and bright lens.

DESCRIPTION OF THE NUMERALS

1 . . . CPU, 2 a . . . ROM, 2 b . . . RAM, 2 c . . . memory, 3 . . . system bus, 4 . . . interface, 5 . . . interface, 6 . . . frame grabber, 7 . . . operation device, 8 . . . external connections ports, 9 . . . GPU, 10 . . . GPU, memory, 11 . . . frame buffer, 12 . . . frame buffer, 13 . . . indication output circuit, 14 . . . display, 15 . . . display picture, 16 . . . reading pattern, 16 a . . . reading pattern, 17 . . . aim pixel, 17 a . . . aim pixel 

1. An image processing device which converts brightness of an image by an image scanning in one pass, comprising: Means for determining a histogram (hist i) of brightness information (i) about a moving area of a predetermined pattern including a scanning position of the image scanning; Means for determining cumulative frequencies (n) by accumulating the histogram (hist i) in a range of i≦p, where p is a brightness information before conversion of a scanning position; and Means for converting the brightness information (p) of the scanning position into brightness information depending on the cumulative frequencies (n).
 2. An image processing device for processing every frame of a moving or still image, comprising: an uptake device to take image data of a pixel unit from an image which photographed a subject; a histogram generator to generate a histogram of brightness after having disintegrated the data in a particular color space; and a processor which reads out the image by a predetermined pattern according to color, then determines the brightness of the pixel of the particular position of the pattern based on the histogram, wherein the brightness of the pixel is calculated based on an algorithm that assumes a loop number of times a pixel value.
 3. The image processing device according to claim 2, wherein the processor moves a pixel and a predetermined pattern according to a predetermined rule.
 4. The image processing device according to claim 3, wherein the predetermined rule involves setting the brightness of the pixel of the particular position, when generating the histogram of the predetermined pattern after the movement, subtracting a histogram of the pixel which is not duplicated by prior or after movement, and adding only a histogram of a pixel newly added to the area of the predetermined pattern.
 5. The image processing device according to claim 3, wherein the predetermined rule involves moving the pixel and the predetermined pattern so as to maintain a predetermined overlap portion when the entire predetermined pattern is in a display area. 